mlsanityData to 14 Oct 2026

More Efficient Identifiability Verification in ODE Models by Reducing Non-Identifiability

arXiv 2204.01623 ↗First posted 4 Apr 2022cs.SC cs.LG math.AGcited by 0

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Abstract (arXiv)

Structural global parameter identifiability indicates whether one can determine a parameter's value from given inputs and outputs in the absence of noise. If a given model has parameters for which there may be infinitely many values, such parameters are called non-identifiable. We present a procedure for accelerating a global identifiability query by eliminating algebraically independent non-identifiable parameters. Our proposed approach significantly improves performance across different computer algebra frameworks.

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References · 6

  1. 2021Differential elimination for dynamical models via projections with applications to structural identifiabilitycited by 5
  2. 2018Global Identifiability of Differential Modelscited by 3
  3. 2018SIAN: software for structural identifiability analysis of ODE modelscited by 3
  4. 2021Web-based Structural Identifiability Analyzercited by 3
  5. 2020Computing all identifiable functions of parameters for ODE modelscited by 2
  6. 2020Multi-experiment parameter identifiability of ODEs and model theorycited by 1

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